Triple
T14409560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Double or Nothing |
E357287
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | In Tune |
E272219
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: In Tune | Statement: [Double or Nothing, hasPart, In Tune]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: In Tune Context triple: [Double or Nothing, hasPart, In Tune]
-
A.
In Tune
chosen
In Tune is a long-running BBC Radio 3 magazine programme featuring live classical music performances, interviews with musicians, and arts news.
-
B.
Tune
Tune is the surname of American actor, dancer, singer, theatre director, and choreographer Tommy Tune.
-
C.
Tune
Tune is a historic Viking ship burial site in Norway, notable for yielding one of the earliest known Viking ships, the Tune ship.
-
D.
Borrowed Tune
Borrowed Tune is a reflective, piano-driven song by Neil Young, noted for its vulnerable lyrics and its melody borrowed from the Rolling Stones’ “Lady Jane.”
-
E.
The Tune-Up
The Tune-Up is a podcast cohosted by musician and radio personality Benny Horowitz, featuring conversations that blend music, culture, and personal storytelling.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90c9b3448190aec1608836a5e913 |
completed | April 14, 2026, 7:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5524e26c81909424b5ba88b5f330 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:17 a.m.